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Current generation methods, when applied to the Thangka floral and leaf dataset, struggle to meet its specific compositional and color restoration requirements. To address these issues, the adversarial ResNet with omni\u2010dimensional dynamic convolution\u2010pixel2stylepixel (AROD\u2010PSP) model is proposed. This model uses hand\u2010drawn sketches to guide the generation of floral and leaf elements in Thangka, restoring its artistic features. A lightweight improvement to the encoder network is made; omni\u2010dimensional dynamic convolution (ODConv) is introduced to enhance feature extraction capabilities and increase result diversity; a latent code discriminator is added to ensure that the generated images align more closely with the compositional rules of the dataset; and a colour correction module is employed to adjust the colours, making them more similar to the original images. This approach successfully achieves intelligent design and visual creation tasks for Thangka floral and leaf elements. In comparative experiments, the model achieved second\u2010best results in quantitative analysis and the best performance in qualitative analysis. The model's generalization ability is demonstrated using two public datasets.<\/jats:p>","DOI":"10.1049\/ipr2.70252","type":"journal-article","created":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T14:27:43Z","timestamp":1763994463000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Semi\u2010Interactive Thangka Floral and Leaf Element Image Generation Network Based on Hand\u2010Drawn Sketches"],"prefix":"10.1049","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-6673-2743","authenticated-orcid":false,"given":"Da","family":"Sun","sequence":"first","affiliation":[{"name":"School of Computer Science Qinghai Normal University  Xining Qinghai China"},{"name":"The State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Normal University  Xining Qinghai China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science Qinghai Normal University  Xining Qinghai China"},{"name":"The State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Normal University  Xining Qinghai China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer and Information Hefei University of Technology  Hefei China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8289-5092","authenticated-orcid":false,"given":"Chunyan","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer Science Qinghai Normal University  Xining Qinghai China"},{"name":"The State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Normal University  Xining Qinghai China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"265","published-online":{"date-parts":[[2025,11,24]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"e_1_2_10_3_1","unstructured":"T.Karras T.Aila S.Laine andJ.Lehtinen Progressive Growing of GANs for Improved Quality Stability and Variation arXiv:1710.10196 2018."},{"key":"e_1_2_10_4_1","doi-asserted-by":"crossref","unstructured":"T.Karras S.Laine andT.Aila \u201cA Style\u2010Based Generator Architecture for Generative Adversarial Networks \u201d inProceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(2019).","DOI":"10.1109\/CVPR.2019.00453"},{"key":"e_1_2_10_5_1","doi-asserted-by":"crossref","unstructured":"T.Karras S.Laine M.Aittala J.Hellsten J.Lehtinen andT.Aila \u201cAnalyzing and Improving the Image Quality of Stylegan \u201d inProceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(2020).","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"e_1_2_10_6_1","unstructured":"T.Karras M.Aittala S.Laine et\u00a0al. \u201cAlias\u2010Free Generative Adversarial Networks \u201dAdvances in Neural Information Processing Systems34(2021):852\u2013863."},{"key":"e_1_2_10_7_1","unstructured":"D. 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